Reinforcement learning algorithms help AI reach goals by rewarding desirable actions. Real-world applications, like healthcare, can benefit from reinforcement learning's adaptability. Initial setup ...

Reinforcement-learning algorithms in systems like ChatGPT or Google’s Gemini can work wonders, but they usually need hundreds of thousands of shots at a task before they get good at it. That’s why ...

This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...

Researchers at the University of Science and Technology of China have developed a new reinforcement learning (RL) framework that helps train large language models (LLMs) for complex agentic tasks ...

Reinforcement learning is a subfield of machine learning concerned with how an intelligent agent can learn through trial and error to make optimal decisions in its ...

Melbourne, Australia - 12 August 2025 - Researchers have demonstrated that brain cells learn faster and carry out complex networking more effectively than machine learning by comparing how both a ...

This system utilizes machine learning algorithms to optimize the operation of particle accelerators, reducing manual intervention and enhancing precision in real-time control. By integrating virtual ...

Ben Khalesi writes about where artificial intelligence, consumer tech, and everyday technology intersect for Android Police. With a background in AI and Data Science, he’s great at turning geek speak ...

After millions of games, machine learning algorithms found creative solutions and unexpected new strategies that could transfer to the real world. The Quanta Newsletter ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...